Minimal cut sets identification by hierarchical differential evolution
Résumé
Minimal cut sets (mcs) identification in Fault Trees (FTs) of large, real systems is not trivial. In this work, we transform the problem of mcs identification into an optimization problem. We do so by hierarchically looking for the minimum combination of cut sets that can guarantee the best coverage of all the minterms that make the system fail. A multiple-population, parallel search policy based on a Differential Evolution (DE) algorithm is developed and applied to a case study considering the Airlock System (AS) of a CANDU reacto